Digital Innovation in Forest Science: Applications of Artificial Intelligence, Remote Sensing and Smart Monitoring Systems for Ecosystem Conservation

The integration of digital technologies and artificial intelligence (AI) in forestry is revolutionizing traditional forest management practices worldwide. This comprehensive review examines the current state, applications, challenges, and future prospects of digital forestry technologies, including remote sensing, unmanned aerial vehicles (UAVs), Light Detection and Ranging (LiDAR) systems, Internet of Things (IoT) sensors, machine learning algorithms, and emerging technologies such as blockchain and digital twins. Digital forestry encompasses precision forest inventory, real-time forest health monitoring, automated species classification, wildfire detection and management, and sustainable forest resource planning. Recent advances in machine learning approaches, particularly deep learning models like PointNet++, PointMLP, and convolutional neural networks, have demonstrated exceptional accuracy rates exceeding 95% in tree species classification using UAV-LiDAR data. IoT sensor networks enable continuous monitoring of forest parameters including temperature, humidity, soil moisture, and air quality, facilitating early detection of forest disturbances. Blockchain technology ensures transparent and traceable forest supply chains, combating illegal logging and supporting deforestation-free certification